Data engineering and cloud infrastructure services on Azure and Databricks
Gloify is a data and cloud engineering services firm built around a modern Azure + Databricks stack (Python, PySpark, Spark Structured Streaming, Delta Lake, Kafka, MLflow). The hiring profile—6 senior engineers and data professionals across 8 open roles—signals a shift toward delivery of complex data pipelines and monitoring infrastructure rather than traditional consulting. Active projects center on CI/CD automation, system health monitoring, and Grafana dashboards, while internal pain points (data latency, capacity planning, performance optimization at scale) suggest deep experience with the problems their clients face.
Gloify is a digital transformation and cloud services company headquartered in Bengaluru, founded in 2017. The firm works with clients globally across web development, DevOps, and digital marketing, with stated engagement of more than 90 clients. Recent hiring velocity and project portfolio indicate a narrowing focus toward data engineering and cloud platform services, particularly Azure infrastructure optimization and observability solutions. The 51–200-person organization operates entirely from India.
Python, PySpark, SQL, Databricks, Apache Spark Structured Streaming, Delta Lake, Kafka, Azure (Data Lake Storage, Synapse Analytics, Data Factory, Functions), Snowflake, MLflow, TensorFlow, Docker, Git, CI/CD, Terraform, Ansible, and Grafana.
Building CI pipelines, automated system health monitoring, Azure infrastructure optimization, and Grafana-based interactive dashboards and monitoring solutions integrated with Azure services.
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